Model-based patterns in prostate cancer mortality worldwide.
Ontology highlight
ABSTRACT:
SUBMITTER: Fontes F
PROVIDER: S-EPMC3681014 | biostudies-other | 2013 Jun
REPOSITORIES: biostudies-other
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2017-08-01 | GSE101431 | GEO
Project description:BACKGROUND:Spatial heterogeneity of prostate cancer-specific mortality in Pennsylvania remains unclear. We utilized advanced geospatial survival regressions to examine spatial variation of prostate cancer-specific mortality in PA and evaluate potential effects of individual- and county-level risk factors. METHODS:Prostate cancer cases, aged ?40?years, were identified in the 2004-2014 Pennsylvania Cancer Registry. The 2018 County Health Rankings data and the 2014?U.S. Environmental Protection Agency's Environmental Quality Index were used to extract county-level data. The accelerated failure time models with spatial frailties for geographical correlations were used to assess prostate cancer-specific mortality rates for Pennsylvania and by the Penn State Cancer Institute (PSCI) 28-county catchment area. Secondary assessment based on estimated spatial frailties was conducted to identify potential health and environmental risk factors for mortality. RESULTS:There were 94,274 cases included. The 5-year survival rate in PA was 82% (95% confidence interval, CI: 81.1-82.8%), with the catchment area having a lower survival rate 81% (95% CI: 79.5-82.6%) compared to the non-catchment area rate of 82.3% (95% CI: 81.4-83.2%). Black men, uninsured, more aggressive prostate cancer, rural and urban Appalachia, positive lymph nodes, and no definitive treatment were associated with lower survival. Several county-level health (i.e., poor physical activity) and environmental factors in air and land (i.e., defoliate chemical applied) were associated with higher mortality rates. CONCLUSIONS:Spatial variations in prostate cancer-specific mortality rates exist in Pennsylvania with a higher risk in the PSCI's catchment area, in particular, rural-Appalachia. County-level health and environmental factors may contribute to spatial heterogeneity in prostate cancer-specific mortality.
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Project description:Men diagnosed with nonmetastatic prostate cancer have a long life expectancy, and many die of unrelated causes. It is therefore important to know to what extent post-diagnostic diet may affect disease-specific and overall mortality. A total of 926 men participating in the Physicians' Health Study diagnosed with nonmetastatic prostate cancer completed diet questionnaires for a median of 5.1 years after diagnosis, and were followed thereafter to assess mortality for a median of 9.9 years since questionnaire completion. Two post-diagnostic dietary patterns were identified: a Prudent pattern, characterized by higher intake of vegetables, fruits, fish, legumes, and whole grains; and a Western pattern, characterized by higher intake of processed and red meats, high-fat dairy and refined grains. Cox regression was used to estimate multivariable-adjusted hazard ratios (HR) and 95% confidence intervals (CI). During 8,093 person-years of follow-up, 333 men died, 56 (17%) of prostate cancer. The Western pattern was significantly related to a higher risk of prostate cancer-specific and all-cause mortality. Comparing men in the highest versus the lowest quartile of the Western pattern, the HRs were 2.53 (95% CI, 1.00-6.42; Ptrend = 0.02) for prostate cancer-specific mortality and 1.67 (95% CI, 1.16-2.42; Ptrend = 0.01) for all-cause mortality. The Prudent pattern was associated with a significantly lower all-cause mortality (HRQuartile 4 vs. Quartile 1: 0.64; 95% CI, 0.44-0.93; Ptrend = 0.02); the relationship with prostate cancer-specific mortality was inverse but not statistically significant. A post-diagnostic Western dietary pattern was associated with higher prostate cancer-specific and all-cause mortality, whereas a Prudent dietary pattern was related to lower all-cause mortality after prostate cancer diagnosis.
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Project description:Prostate cancer (PCa) incidence and mortality vary across territories and populations. This can be explained by the genetic factor of this disease. This article aims to correlate the epidemiological data, worldwide incidence, and mortality of PCa with single-nucleotide polymorphisms (SNPs) associated with the susceptibility and severity of this neoplasm in different populations. Eighty-four genetic variants associated with prostate cancer susceptibility were selected from the literature through genome association studies (GWAS). Allele frequencies were obtained from the 1000 Genomes Project, and epidemiological data were obtained from Surveillance, Epidemiology, and End Results (SEER). The PCa incidence, mortality rates, and allele frequencies of variants were evaluated by Pearson's correlation. Our study demonstrated that 12 SNPs (rs2961144, rs1048169, rs7000448, rs4430796, rs2066827, rs12500426, rs6983267, rs11649743, rs2075110, rs114798100, rs855723, and rs2075109) were correlated with epidemiological data in different ethnic groups. Ten SNPs (rs2961144, rs1048169, rs7000448, rs4430796, rs2066827, rs12500426, rs11649743, rs2075110, rs114798100, and rs2075109) were positively correlated with the mortality rate. Seven SNPs (rs1048169, rs2961144, rs7000448, rs4430796, rs2066827, rs12500426, and rs114798100) were positively correlated with incidence. Positive correlations of incidence and mortality rates were more frequent in the African population. The genetic variants investigated here are likely to predispose to PCa and could play a role in its progression and aggressiveness. This genetic study demonstrated here is promising for implementing personalized strategies to screen for prostate cancer in diverse populations.
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Project description:The aim of this study is to evaluate all-cause mortality risk differences before and during prostate cancer screening, with a profound focus on the differences between screened and not-screened patient groups. Prostate cancer cases diagnosed between 1998 and 2016 were identified from the population-based Lithuanian Cancer Registry and linked with screening status in the National Health Insurance Fund database. The analysis was stratified by a period of diagnosis and screening status. Standardized mortality ratios (SMRs) were used to assess all-cause and cause-specific mortality risk. The SMRs were calculated by dividing the observed number of deaths among prostate cancer patients by the expected number of deaths from the general population. All-cause SMR (1.45 (95% CI 1.42-1.48)) in the pre-screening period was higher compared to the screening period (SMR = 1.17 (95% CI 1.15-1.19)). An increased all-cause mortality risk among prostate cancer patients was observed in the not-screened patient population (SMR = 1.76 (95% CI 1.71-1.82)), while all-cause mortality risk in the screened patient population was similar to the general population (SMR = 1.00 (95% CI 0.97-1.02)). Screened patients with localized stage of disease had lower all-cause mortality risk than the general population (SMR = 0.72 (95% CI 0.70-0.75)). In conclusion, men with prostate cancer in Lithuania had excess all-cause mortality risk compared to the general population. The all-cause mortality risk among screened patients was not higher than expected.
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Project description:BackgroundGleason grading of prostate cancer is an important prognostic factor, but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial intelligence (A.I.) tools have demonstrated Gleason grading on-par with expert pathologists, it remains an open question whether and to what extent A.I. grading translates to better prognostication.MethodsIn this study, we developed a system to predict prostate cancer-specific mortality via A.I.-based Gleason grading and subsequently evaluated its ability to risk-stratify patients on an independent retrospective cohort of 2807 prostatectomy cases from a single European center with 5-25 years of follow-up (median: 13, interquartile range 9-17).ResultsHere, we show that the A.I.'s risk scores produced a C-index of 0.84 (95% CI 0.80-0.87) for prostate cancer-specific mortality. Upon discretizing these risk scores into risk groups analogous to pathologist Grade Groups (GG), the A.I. has a C-index of 0.82 (95% CI 0.78-0.85). On the subset of cases with a GG provided in the original pathology report (n = 1517), the A.I.'s C-indices are 0.87 and 0.85 for continuous and discrete grading, respectively, compared to 0.79 (95% CI 0.71-0.86) for GG obtained from the reports. These represent improvements of 0.08 (95% CI 0.01-0.15) and 0.07 (95% CI 0.00-0.14), respectively.ConclusionsOur results suggest that A.I.-based Gleason grading can lead to effective risk stratification, and warrants further evaluation for improving disease management.
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Project description:BackgroundCancer is widely recognized as a global public health problem. Breast, prostate, and cervical cancer are among the most frequent types in developing countries. Assessing their incidence and mortality by regions and municipalities is important to guide evidence-based health policy. Our aim was to describe the incidence and mortality trends for breast, cervical, and prostate cancer across regions and municipalities in Colombia during 2018.MethodsWe performed a cross-sectional analysis with data from people with breast, prostate, or cervical cancer, reported to the National Administrative Cancer Registry during 2018. A descriptive analysis was performed. Age-standardized incidence and mortality rates were estimated at national, regional, and municipal levels. Finally, we identify the regions and municipalities with significantly higher or lower incidence and mortality rates compared to national estimations.ResultsBreast cancer was the most frequent type among all new cases and deaths in Colombia. Breast, prostate and cervical cancer incidence and mortality rates per 100,000 were: 18.69 (CI 95%: 18.15-19.25) and 10.48 (CI 95%: 10.07-10.91); 11.34 (CI 95%: 10.90-11.78) and 7.58 (CI 95%: 7.22-7.96); 5.93 (CI 95%: 5.62-6.25) and 4.31 (CI 95%: 4.05-4.58), respectively. Eastern region had both, incidence and mortality rates, significantly lower than national for all types of cancer. By municipalities, there was a heterogeneous pattern. Nonetheless, Agua de Dios (Cundinamarca), had one of the highest incidence rates for all types.ConclusionsWe observed clear differences in cancer incidence and mortality across regions and municipalities, depending on each type of cancer. Our findings are important to improve screening coverage, early detection, and treatment in the country.
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Project description:DNA methylation is an epigenetic modification, influenced by both genetic and environmental variation, that plays a key role in transcriptional regulation and many organismal phenotypes. Although patterns of DNA methylation have been shown to differ between human populations, it remains to be determined how epigenetic diversity relates to the patterns of genetic and gene expression variation at a global scale. Here we measured DNA methylation at 485,000 CpG sites in five diverse human populations, and analysed these data together with genome-wide genotype and gene expression data. We found that population-specific DNA methylation mirrors genetic variation, and has greater local genetic control than mRNA levels. We estimated the rate of epigenetic divergence between populations, which indicates far greater evolutionary stability of DNA methylation in humans than has been observed in plants. This study provides a deeper understanding of worldwide patterns of human epigenetic diversity, as well as initial estimates of the rate of epigenetic divergence in recent human evolution.
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